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Robustness of bootstrap in instrumental variable regression

Camponovo, Lorenzo; Otsu, Taisuke - In: Econometric reviews 34 (2015) 1/5, pp. 352-393

Persistent link: https://www.econbiz.de/10011373276

Strategic behavior in regressions: an experimental study

Perote, Javier; Perote-Peña, Juan; Vorsatz, Marc - In: Theory and decision : an international journal for … 79 (2015) 3, pp. 517-546

Persistent link: https://www.econbiz.de/10011377513

Robust estimation and inference for threshold models with integrated regressors

Chen, Haiqiang - In: Econometric theory 31 (2015) 4, pp. 778-810

Persistent link: https://www.econbiz.de/10011341927

Regression and kriging metamodels with their experimental designs in simulation : review

Kleijnen, Jack P. C. - 2015

Persistent link: https://www.econbiz.de/10011349935

Robust estimation and inference for threshold models with integrated regressors

Chen, Haiqiang - 2013

This paper studies the robust estimation and inference of threshold models with integrated regres- sors. We derive the asymptotic distribution of the profiled least squares (LS) estimator under the diminishing threshold effect assumption that the size of the threshold effect converges to zero....

Persistent link: https://www.econbiz.de/10009767269

Computing the update of the repeated median regression line in linear time

Bernholt, Thorsten; Fried, Roland - 2002

The repeated median line estimator is a highly robust method for fitting a regression line to a set of n data points in the plane. In this paper, we consider the problem of updating the estimate after a point is removed from or added to the data set. This problem occurs e.g. in statistical...

Persistent link: https://www.econbiz.de/10009770914

Due diligence in meta-analyses to support benefit transfers

Boyle, Kevin J.; Parmeter, Christopher F.; Boehlert, … - In: Environmental & resource economics : the official … 55 (2013) 3, pp. 357-386

Persistent link: https://www.econbiz.de/10009753954

Robust estimation in nonlinear regression and limited dependent variable models

Čížek, Pavel - 2001

Classical parametric estimation methods applied to nonlinear regression and limited-dependent-variable models are very sensitive to misspecification and data errors. On the other hand, semiparametric and nonparametric methods, which are not restricted by parametric assumptions, require more data...

Persistent link: https://www.econbiz.de/10009618360

Smoothed influence function : another view at robust nonparametric regression

Tamine, Julien - 2001

In this work, we introduce a smoothed influence function that constitute a theoretical tool for studying the outliers robustness properties of a large class of nonparametric estimators. With this tool, we first show the nonrobustness of the Nadaraya-Watson estimator of regression. Then we show...

Persistent link: https://www.econbiz.de/10009626684

Simultaneous robust estimation of multi-response surfaces in the presence of outliers

Bashiri, Mahdi; Moslemi, Amir - In: Journal of industrial engineering international 9 (2013), pp. 1-12

are derived from the least squares method. Because the presence of outlier data is unavoidable in most real cases and …-response surfaces, an individual estimation of each response can cause a problem in future deductions because of separate outlier … suggested. By presenting a coincident outlier index (COI) criterion while considering a realistic number of outliers in a multi …

Persistent link: https://www.econbiz.de/10009759158